import os
from collections.abc import Generator

import pytest

from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta
from core.model_runtime.entities.message_entities import (
    AssistantPromptMessage,
    ImagePromptMessageContent,
    SystemPromptMessage,
    TextPromptMessageContent,
    UserPromptMessage,
)
from core.model_runtime.errors.validate import CredentialsValidateFailedError
from core.model_runtime.model_providers.ollama.llm.llm import OllamaLargeLanguageModel


def test_validate_credentials():
    model = OllamaLargeLanguageModel()

    with pytest.raises(CredentialsValidateFailedError):
        model.validate_credentials(
            model="mistral:text",
            credentials={
                "base_url": "http://localhost:21434",
                "mode": "chat",
                "context_size": 2048,
                "max_tokens": 2048,
            },
        )

    model.validate_credentials(
        model="mistral:text",
        credentials={
            "base_url": os.environ.get("OLLAMA_BASE_URL"),
            "mode": "chat",
            "context_size": 2048,
            "max_tokens": 2048,
        },
    )


def test_invoke_model():
    model = OllamaLargeLanguageModel()

    response = model.invoke(
        model="mistral:text",
        credentials={
            "base_url": os.environ.get("OLLAMA_BASE_URL"),
            "mode": "chat",
            "context_size": 2048,
            "max_tokens": 2048,
        },
        prompt_messages=[UserPromptMessage(content="Who are you?")],
        model_parameters={"temperature": 1.0, "top_k": 2, "top_p": 0.5, "num_predict": 10},
        stop=["How"],
        stream=False,
    )

    assert isinstance(response, LLMResult)
    assert len(response.message.content) > 0


def test_invoke_stream_model():
    model = OllamaLargeLanguageModel()

    response = model.invoke(
        model="mistral:text",
        credentials={
            "base_url": os.environ.get("OLLAMA_BASE_URL"),
            "mode": "chat",
            "context_size": 2048,
            "max_tokens": 2048,
        },
        prompt_messages=[
            SystemPromptMessage(
                content="You are a helpful AI assistant.",
            ),
            UserPromptMessage(content="Who are you?"),
        ],
        model_parameters={"temperature": 1.0, "top_k": 2, "top_p": 0.5, "num_predict": 10},
        stop=["How"],
        stream=True,
    )

    assert isinstance(response, Generator)

    for chunk in response:
        assert isinstance(chunk, LLMResultChunk)
        assert isinstance(chunk.delta, LLMResultChunkDelta)
        assert isinstance(chunk.delta.message, AssistantPromptMessage)


def test_invoke_completion_model():
    model = OllamaLargeLanguageModel()

    response = model.invoke(
        model="mistral:text",
        credentials={
            "base_url": os.environ.get("OLLAMA_BASE_URL"),
            "mode": "completion",
            "context_size": 2048,
            "max_tokens": 2048,
        },
        prompt_messages=[UserPromptMessage(content="Who are you?")],
        model_parameters={"temperature": 1.0, "top_k": 2, "top_p": 0.5, "num_predict": 10},
        stop=["How"],
        stream=False,
    )

    assert isinstance(response, LLMResult)
    assert len(response.message.content) > 0


def test_invoke_stream_completion_model():
    model = OllamaLargeLanguageModel()

    response = model.invoke(
        model="mistral:text",
        credentials={
            "base_url": os.environ.get("OLLAMA_BASE_URL"),
            "mode": "completion",
            "context_size": 2048,
            "max_tokens": 2048,
        },
        prompt_messages=[
            SystemPromptMessage(
                content="You are a helpful AI assistant.",
            ),
            UserPromptMessage(content="Who are you?"),
        ],
        model_parameters={"temperature": 1.0, "top_k": 2, "top_p": 0.5, "num_predict": 10},
        stop=["How"],
        stream=True,
    )

    assert isinstance(response, Generator)

    for chunk in response:
        assert isinstance(chunk, LLMResultChunk)
        assert isinstance(chunk.delta, LLMResultChunkDelta)
        assert isinstance(chunk.delta.message, AssistantPromptMessage)


def test_invoke_completion_model_with_vision():
    model = OllamaLargeLanguageModel()

    result = model.invoke(
        model="llava",
        credentials={
            "base_url": os.environ.get("OLLAMA_BASE_URL"),
            "mode": "completion",
            "context_size": 2048,
            "max_tokens": 2048,
        },
        prompt_messages=[
            UserPromptMessage(
                content=[
                    TextPromptMessageContent(
                        data="What is this in this picture?",
                    ),
                    ImagePromptMessageContent(
                        data=""
                    ),
                ]
            )
        ],
        model_parameters={"temperature": 0.1, "num_predict": 100},
        stream=False,
    )

    assert isinstance(result, LLMResult)
    assert len(result.message.content) > 0


def test_invoke_chat_model_with_vision():
    model = OllamaLargeLanguageModel()

    result = model.invoke(
        model="llava",
        credentials={
            "base_url": os.environ.get("OLLAMA_BASE_URL"),
            "mode": "chat",
            "context_size": 2048,
            "max_tokens": 2048,
        },
        prompt_messages=[
            UserPromptMessage(
                content=[
                    TextPromptMessageContent(
                        data="What is this in this picture?",
                    ),
                    ImagePromptMessageContent(
                        data=""
                    ),
                ]
            )
        ],
        model_parameters={"temperature": 0.1, "num_predict": 100},
        stream=False,
    )

    assert isinstance(result, LLMResult)
    assert len(result.message.content) > 0


def test_get_num_tokens():
    model = OllamaLargeLanguageModel()

    num_tokens = model.get_num_tokens(
        model="mistral:text",
        credentials={
            "base_url": os.environ.get("OLLAMA_BASE_URL"),
            "mode": "chat",
            "context_size": 2048,
            "max_tokens": 2048,
        },
        prompt_messages=[UserPromptMessage(content="Hello World!")],
    )

    assert isinstance(num_tokens, int)
    assert num_tokens == 6
